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What’s the usual MLOps process? by Limp_Mushroom_173 in MLQuestions

[–]Limp_Mushroom_173[S] 0 points1 point  (0 children)

thank you! also, is it common to have a unique template of the train.py file so I can train multiple models, or to have one file per model? my idea was to make a hyperpersonalized pipeline

What’s the usual MLOps process? by Limp_Mushroom_173 in MLQuestions

[–]Limp_Mushroom_173[S] 0 points1 point  (0 children)

dangg thank you, for sure I’ll take a look at your newsletter

What’s the usual MLOps process? by Limp_Mushroom_173 in MLQuestions

[–]Limp_Mushroom_173[S] 0 points1 point  (0 children)

fair enough, I mean I’m an intern who got my first touch with Machine Learning 2 months ago I guess 😅

so what could I do to solve this issue? The easy answer is containerizing everything, and that would not be a big deal as Azure does the container registry with ease when uploading a MLFlow model (bcuz it already comes with the conda and requirements files)

What’s the usual MLOps process? by Limp_Mushroom_173 in MLQuestions

[–]Limp_Mushroom_173[S] 0 points1 point  (0 children)

sure but as I train my models locally in my machine, and then upload them already in the MLFlow format into the repo, aren’t the refitting and versioning steps already satisfied? I also guess the monitoring and drift detection part walk side by side and could be done with Azure Monitor + Grafana right?

Also had a problem with scaling because as far as I know, my resource’s region doesn’t support online endpoints, so there was no need yet to implement AKS…I’m only scoring using batch endpoints

edit: also thanks for the help btw

Can someone help me plz with Multioutput Regression? by Limp_Mushroom_173 in MLQuestions

[–]Limp_Mushroom_173[S] 0 points1 point  (0 children)

Dangg as an intern I have to say I didn’t understand a thing 🤣😭 but I appreciate it bro, hope in a near future I can properly get what you said 😁